The present application finds particular application in commercial vehicle systems, particularly involving motor control in hybrid commercial vehicles. However, it will be appreciated that the described technique may also find application in other motor control systems, other commercial vehicle systems, or other hybrid vehicle systems.
Proportional-integral-derivative (PID) controllers typically comprise a control loop feedback mechanism and are used in control systems (e.g., industrial control systems, automotive control systems, etc.). A PID controller iteratively adjusts one or more parameters (e.g., current, voltage, etc.) to correctly minimize a difference (e.g., error) between a measured process variable and a desired setpoint by determining a corrective action that adjusts the process. Determining the corrective action involves calculating three separate parameter values for the measured error: proportional, integral, and derivative values. The proportional value is used to determine an appropriate reaction to the current error, the integral value is used to determine an appropriate reaction based on the sum of recent errors, and the derivative value is used to determine an appropriate reaction based on the rate at which the error has been changing. The weighted sum of these three values is used to adjust the process via a control element (e.g., a current or voltage source, a valve, etc.).
By tuning the three constants in the PID controller algorithm, a controller can provide a control mechanism tailored for specific process requirements. The response of the controller can be described in terms of the responsiveness of the controller to an error, the degree to which the controller overshoots the setpoint, and/or the degree of system oscillation. However, the use of the PID algorithm for control does not guarantee optimal control of the system or system stability, and cannot account for unexpected system disturbances (e.g., motor stall, short circuit, etc.).
Not all applications require all three control variables or modes, but rather some applications may use only one or two modes to provide the desired system control. This is achieved by setting the gain of undesired control output(s) to zero. For example, if the derivative gain is set to zero, then the PID controller becomes a PI controller. PI controllers are particularly common, since derivative action is very sensitive to measurement noise, and since the absence of an integral value can prevent the system from reaching its target value due to the control action.
PID controllers are used in the automotive industry to control various systems. A major drawback of PID controllers is that they are typically effective only over a relatively narrow range of system parameters. Despite tuning improvements such as pole placement, fuzzy logic, auto-tuning, gain scheduling, adaptation, etc., PID controllers remain less than optimal when employed to control a motor or system over a wide range of operating parameters. Attempts to adapt a PID controller over wide ranges of system parameters or variables result in suboptimal performance.
The present application provides new and improved motor control systems and methods for hybrid commercial vehicles, which overcome the above-referenced problems and others.